CN112710899B - Power grid signal frequency detection method for improving gain finite impulse response filtering - Google Patents
Power grid signal frequency detection method for improving gain finite impulse response filtering Download PDFInfo
- Publication number
- CN112710899B CN112710899B CN202110329745.2A CN202110329745A CN112710899B CN 112710899 B CN112710899 B CN 112710899B CN 202110329745 A CN202110329745 A CN 202110329745A CN 112710899 B CN112710899 B CN 112710899B
- Authority
- CN
- China
- Prior art keywords
- filter
- signal
- impulse response
- finite impulse
- frequency
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 230000004044 response Effects 0.000 title claims abstract description 40
- 238000001514 detection method Methods 0.000 title claims abstract description 25
- 238000001914 filtration Methods 0.000 title claims abstract description 10
- 238000012937 correction Methods 0.000 claims abstract description 18
- 230000003044 adaptive effect Effects 0.000 claims abstract description 9
- 238000004364 calculation method Methods 0.000 claims abstract description 4
- 238000001228 spectrum Methods 0.000 claims description 14
- 238000000034 method Methods 0.000 claims description 7
- 230000003111 delayed effect Effects 0.000 claims description 6
- 238000005316 response function Methods 0.000 claims description 4
- 230000003595 spectral effect Effects 0.000 claims description 4
- 238000005070 sampling Methods 0.000 claims description 3
- 239000000126 substance Substances 0.000 claims description 2
- 238000004458 analytical method Methods 0.000 description 6
- 238000005259 measurement Methods 0.000 description 6
- 238000010586 diagram Methods 0.000 description 2
- 238000012545 processing Methods 0.000 description 2
- 108010003272 Hyaluronate lyase Proteins 0.000 description 1
- 238000003491 array Methods 0.000 description 1
- 238000013473 artificial intelligence Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 230000010354 integration Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 238000010606 normalization Methods 0.000 description 1
- 238000005457 optimization Methods 0.000 description 1
- 238000010248 power generation Methods 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
- 238000010183 spectrum analysis Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 230000001629 suppression Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R23/00—Arrangements for measuring frequencies; Arrangements for analysing frequency spectra
- G01R23/16—Spectrum analysis; Fourier analysis
- G01R23/165—Spectrum analysis; Fourier analysis using filters
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R23/00—Arrangements for measuring frequencies; Arrangements for analysing frequency spectra
- G01R23/02—Arrangements for measuring frequency, e.g. pulse repetition rate; Arrangements for measuring period of current or voltage
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R23/00—Arrangements for measuring frequencies; Arrangements for analysing frequency spectra
- G01R23/16—Spectrum analysis; Fourier analysis
- G01R23/175—Spectrum analysis; Fourier analysis by delay means, e.g. tapped delay lines
Abstract
The invention provides a power grid signal frequency detection method for improving gain finite impulse response filtering, which is used for detecting a detected signal x [ n ]]Respectively inputting the improved gain finite impulse response filter S and the self-adaptive delay phase offset correction unit D, and setting the output of the improved gain finite impulse response filter S as y [ n ]]The output of the adaptive delay phase offset correction unit D is xD[n]Respectively mixing y [ n ]]And xD[n]Inputting the average signal into a low-pass average filter with the length of N to respectively obtain outputs Ay[n]And Ax[n]Calculating Ay[n]And Ax[n]And after the ratio is obtained, the fast detection of the signal frequency is realized by applying a filter frequency response gain calculation formula. On one hand, the stability of the frequency detection result can be ensured; on the other hand, high accuracy of the frequency detection result can be ensured.
Description
Technical Field
The invention relates to the field of power grid signal filtering and frequency detection, in particular to a power grid signal frequency detection method for improving gain finite impulse response filtering.
Background
The frequency reflects the dynamic balance between power generation and load, is one of the most basic parameters of the power system, and accurate and rapid frequency measurement has important significance for the operation, monitoring and control of the power system. The essence of the grid frequency measurement is parameter estimation of a sinusoidal signal model, i.e. the frequency of a signal is estimated by signal processing and numerical analysis methods using the signal of the system as input, such as voltage or current.
Frequency measurement, while dominant in algorithm design and implementation, secondary algorithms largely determine whether they can be expected to perform and the reliability of the device. The selection of the appropriate secondary algorithm is mainly determined by the signal model, the frequency characteristics required for subsequent control or analysis, the computing power of the primary algorithm, the response time, the accuracy requirement, software and hardware constraints, and the like. With the deep knowledge of the dynamic behavior of the power system, frequency measurement has been developed from early zero-crossing detection to the current methods based on digital signal processing and artificial intelligence. The algorithms have advantages and disadvantages in the aspects of noise interference resistance, harmonic suppression, stable dynamic measurement precision, response time, calculation complexity and the like, the range of the algorithms covers time domain analysis, frequency domain analysis and time-frequency joint analysis, and the implementation strategies comprise nonlinear problem linearization, mathematical optimization, self-adaptation, algorithm combination integration and the like. Some hardware techniques, such as phase-locked loops, digital frequency multipliers, field programmable gate arrays, etc., are also used in the frequency real-time measurement. Practice shows that it is not easy to obtain an auxiliary algorithm which has small time lag and strong denoising capability and can provide high-precision frequency characteristics for subsequent control analysis.
Disclosure of Invention
In order to overcome the defects of the prior art, the invention provides a power grid signal frequency detection method for improving gain finite impulse response filtering, and the technical problem solved by the invention is how to carry out frequency fast detection through a filter and expansion characteristics without carrying out complex spectrum analysis on signals, reducing operations such as Fourier transform or wavelet transform and the like.
In order to solve the technical problems, the solution proposed by the invention is as follows: the signal x n to be detected]Respectively inputting the improved gain finite impulse response filter S and the self-adaptive delay phase offset correction unit D, wherein n is the mark number of the signal discrete sequence, and the output of the improved gain finite impulse response filter S is set as y [ n [ ]]The output of the adaptive delay phase offset correction unit D is xD[n]Respectively mixing y [ n ]]And xD[n]Input to a low-pass average filter RA with a length N to obtain outputs Ay[n]And Ax[n]Calculating Ay[n]And Ax[n]After the ratio is obtained, the fast detection of the signal frequency can be realized by applying a filter frequency response gain calculation formula.
Further, the improved gain finite impulse response filter S is constructed by the following steps:
step 1, calculating an I-type finite impulse response filter h [ N ] with the length of N =2M +1, satisfying h [ N ] = h [ -N ], -M ≦ N ≦ M, wherein M is a positive integer, and the frequency response function is
Wherein the angular frequency ω =2 π f;
step 2, for h [ n ]]Carrying out p +1 times of self convolution operation, wherein p is a positive integer, and obtaining a p-order convolution filter hp[n]：
Step 3, for hp[n]Performing time domain expansion to expandIts impulse response, i.e. by inserting zeros between the filter samples:
the value range of the expansion factor L is a positive integer, the special condition that zero is not inserted is adopted when L =1, and the sequence is obtained after time domain expansion of the inserted zero
The sequence is the modified gain finite impulse response filter S.
Further, the adaptive delay phase offset correction unit D includes:
step 1, for the detected signalx[n]Performing fast Fourier transform on the discrete magnitude spectrumXFinding out the peak spectral line, and obtaining the discrete phase spectrum according to the serial number of the discrete peak spectral linePAccording to the Fourier spectrum theory expression, the detected signal is obtainedx[n]Initial phase rough estimation ofϕ s1；
Step 2, setting a delay coefficient asr，rIs an integer and takes a value less than the detected signalx[n]Length ofNOne half of (1) to the signalx[n]Performing time delay operation to obtain delayed signalx r [n]；
Step 3, the signals after time delay are processedx r [n]Performing fast Fourier transform to obtain delayed signalx r [n]Initial phase rough estimation ofϕ s2；
Step 4, calculating a delay phase offset correction coefficient u:
step 5, setting the detected signalx[n]At a sampling frequency off s Using time-delayed phaseOffset correction coefficient u for detected signalx[n]Discrete phase spectrum ofPCorrected discrete phase spectrum is obtained by correctionP D ：
Using discrete magnitude spectraXAnd corrected discrete phase spectrumP D Performing inverse discrete Fourier transform, and the output is the output x of the adaptive delay phase offset correction unit DD[n]。
Further, the filter frequency response gain is calculated as
Wherein the content of the first and second substances,
。
further, hp[n]Corresponding frequency response function is
。
The invention has the beneficial effects that:
on one hand, the improved gain finite impulse response filter is constructed on the basis of the I type finite impulse response filter, and the stability of a frequency detection result can be ensured because the I type finite impulse response filter has linear phase response and zero phase offset; on the other hand, time domain expansion is adopted to expand the impulse response of the filter, and gain estimation is further carried out through a low-pass average filter, so that high accuracy of a frequency detection result is ensured.
Drawings
Fig. 1 is a schematic diagram of a power grid signal frequency detection method with improved gain finite impulse response filtering according to the present invention.
Detailed Description
The invention will be described in further detail below with reference to the accompanying drawings and specific embodiments.
In order to verify the power grid signal frequency detection method for improving the gain finite impulse response filtering, the invention provides a power grid signal frequency detection method. According to the schematic diagram of the grid signal frequency detection method for improving the gain finite impulse response filtering shown in FIG. 1, the embodiment selects the I-type finite impulse response filter h [ n ] containing 3 parameters]=[1/4, 1/2, 1/4]The corresponding frequency responses are respectively H (e)j0) =1 and H (e)jπ) =0, corresponding to a convolution filter of order 1 ofh 1[n]=[1/16, 1/4, 3/8, 1/4, 1/16]Taking the spreading factor L =2 to obtain an improved gain finite impulse response filter S ofh 2 1[n]=[1/16, 0,1/4, 0, 3/8, 0,1/4, 0, 1/16]. The delay constant of the adaptive delay phase offset correction unit D is set to 4.
A data acquisition card DAQ-USB 6002 is used for acquiring a sinusoidal signal which is generated by the Agilent signal generator 33120a, has the amplitude of 1V, the frequency of 50.5Hz and the phase of 0 at the sampling frequency of 2000Hz to obtain a sequence x [ n ], and one section of data after reduction and normalization is shown in a table 1.
TABLE 1
The x [ n ] is fed into the improved gain finite impulse response filter S, and the filter output y [ n ] is calculated and shown in Table 2.
TABLE 2
Will signal x [ n ]]Sending the signal into a self-adaptive delay phase deviation correction unit D, and calculating to obtain a filter output xD[n]Respectively mixing y [ n ]]And xD[n]Input to a low-pass average filter RA with a length N to obtain outputs Ay[n]And Ax[n]Calculating Ay[n]And Ax[n]Ratio of
Using filter frequency response gain estimation
The partial detection results of the calculated signal frequencies are shown in table 3. Table 4 shows the comparison of the detection errors of the frequency part of the power grid signal, and it can be seen from table 4 that the error of the method provided by the present invention is at least one order of magnitude smaller than the error of the commonly used hanning window interpolation fourier transform, and the method provided by the present invention has higher accuracy.
TABLE 3
TABLE 4
The foregoing merely represents preferred embodiments of the invention, which are described in some detail and detail, and therefore should not be construed as limiting the scope of the invention. It should be noted that, for those skilled in the art, various changes, modifications and substitutions can be made without departing from the spirit of the present invention, and these are all within the scope of the present invention. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (4)
1. A power grid signal frequency detection method for improving gain finite impulse response filtering is characterized in that: the signal x n to be detected]Respectively sent to a modified gain finite impulse response filter S and an adaptive delay phase offset correction unit D, wherein n is the mark number of the discrete sequence of the signal, and the output of the modified gain finite impulse response filter S is set as y [ n ]]The output of the adaptive delay phase offset correction unit D is xD[n]Respectively mixing y [ n ]]And xD[n]Input to a low-pass average filter of length NA wave filter RA for obtaining outputs Ay[n]And Ax[n]Calculating Ay[n]And Ax[n]After the ratio is obtained, the rapid detection of the signal frequency can be realized by applying a filter frequency response gain calculation formula;
the improved gain finite impulse response filter S is constructed by the following steps:
step 1.1, calculating an I-type finite impulse response filter h [ N ] with the length of N =2M +1, and satisfying h [ N ] = h [ -N ], -M ≦ N ≦ M, wherein M is a positive integer and the frequency response function is
Wherein the angular frequency ω =2 π f;
step 1.2, for h [ n ]]Carrying out p +1 times of self convolution operation, wherein p is a positive integer, and obtaining a p-order convolution filter hp[n]；
Step 1.3, for hp[n]Time domain expansion is performed to extend its impulse response, i.e. by inserting zeros between the filter samples:
the value range of the expansion factor L is a positive integer, the special condition that zero is not inserted is adopted when L =1, and the sequence is obtained after time domain expansion of the inserted zero
The sequence is the modified gain finite impulse response filter S.
2. The method of claim 1, wherein the grid signal frequency detection method comprises: the adaptive delay phase offset correction unit D comprises the following working steps:
step 2.1, for the detected signalx[n]Performing fast Fourier transform on discrete framesDegree spectrumXFinding out the peak spectral line, and obtaining the discrete phase spectrum according to the serial number of the discrete peak spectral linePAccording to the Fourier spectrum theory expression, the detected signal is obtainedx[n]Initial phase rough estimation ofϕ s1；
Step 2.2, setting the delay coefficient asr，rIs an integer and takes a value less than the detected signalx[n]Length ofNOne half of (1) to the signalx[n]Performing time delay operation to obtain delayed signalx r [n]；
Step 2.3, for the delayed signalsx r [n]Performing fast Fourier transform to obtain delayed signalx r [n]Initial phase rough estimation ofϕ s2；
Step 2.4, calculating a delay phase offset correction coefficient u:
step 2.5, setting the detected signalx[n]At a sampling frequency off s Using the delayed phase offset correction coefficient u to the detected signalx[n]Discrete phase spectrum ofPCorrected discrete phase spectrum is obtained by correctionP D ：
Using discrete magnitude spectraXAnd corrected discrete phase spectrumP D Performing inverse discrete Fourier transform, and the output is the output x of the adaptive delay phase offset correction unit DD[n]。
3. The method of claim 1, wherein the grid signal frequency detection method comprises: the filter frequency response gain is calculated as
Wherein the content of the first and second substances,
。
4. the method of claim 1, wherein the grid signal frequency detection method comprises: h isp[n]Corresponding frequency response function is
。
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110329745.2A CN112710899B (en) | 2021-03-29 | 2021-03-29 | Power grid signal frequency detection method for improving gain finite impulse response filtering |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110329745.2A CN112710899B (en) | 2021-03-29 | 2021-03-29 | Power grid signal frequency detection method for improving gain finite impulse response filtering |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN112710899A CN112710899A (en) | 2021-04-27 |
| CN112710899B true CN112710899B (en) | 2021-07-13 |
Family
ID=75550326
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110329745.2A Active CN112710899B (en) | 2021-03-29 | 2021-03-29 | Power grid signal frequency detection method for improving gain finite impulse response filtering |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112710899B (en) |
Family Cites Families (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5578937A (en) * | 1995-03-31 | 1996-11-26 | Martin Marietta Energy Systems, Inc. | Instrument for analysis of electric motors based on slip-poles component |
| KR100847687B1 (en) * | 2006-10-20 | 2008-07-23 | (주)에프씨아이 | Frequency Synthesizer and Frequency Calibration Method |
| CN100554917C (en) * | 2007-09-29 | 2009-10-28 | 南京航空航天大学 | Obtain the method for system features function and signal characteristic value |
| CN201602791U (en) * | 2009-10-22 | 2010-10-13 | 江苏中惠医疗科技股份有限公司 | Self-adaptive dynamic filter |
| WO2013183103A1 (en) * | 2012-06-04 | 2013-12-12 | 三菱電機株式会社 | Frequency characteristic transformation device |
| US9529025B2 (en) * | 2012-06-29 | 2016-12-27 | Covidien Lp | Systems and methods for measuring the frequency of signals generated by high frequency medical devices |
| GB2512935A (en) * | 2013-04-12 | 2014-10-15 | Nordic Semiconductor Asa | Digital Radio Transmissions |
| US20150103961A1 (en) * | 2013-10-14 | 2015-04-16 | Lsi Corporation | Digital frequency band detector for clock and data recovery |
| CN105122752B (en) * | 2014-04-08 | 2018-10-19 | 华为技术有限公司 | Estimate the device and method thereof of frequency shift (FS) |
| CN109669072B (en) * | 2018-12-19 | 2020-04-17 | 清华大学 | Self-adaptive synchronous phasor measurement method for power distribution network |
| CN111381075B (en) * | 2020-04-16 | 2020-12-11 | 华中科技大学 | Method and device for acquiring frequency offset by utilizing pre-fitting phase-locked frequency difference value |
| CN112162144B (en) * | 2020-08-19 | 2023-07-21 | 国网江西省电力有限公司供电服务管理中心 | Power grid frequency rapid measurement method and device based on convolution gain |
-
2021
- 2021-03-29 CN CN202110329745.2A patent/CN112710899B/en active Active
Also Published As
| Publication number | Publication date |
|---|---|
| CN112710899A (en) | 2021-04-27 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108764073B (en) | Acceleration noise filtering and integrating method combined with spectrum energy form fitting | |
| CN105137185A (en) | Frequency domain interpolation electric power harmonic wave analysis method based on discrete Fourier transform | |
| Zhou et al. | Time-domain quasi-synchronous sampling algorithm for harmonic analysis based on Newton's interpolation | |
| CN111046327B (en) | Prony analysis method suitable for low-frequency oscillation and subsynchronous oscillation identification | |
| CN108535613B (en) | Voltage flicker parameter detection method based on combined window function | |
| CN115575707A (en) | Harmonic detection device and method based on combination of improved FFT algorithm and wavelet transform | |
| CN111984920A (en) | Subsynchronous/supersynchronous harmonic parameter identification method, subsynchronous/supersynchronous harmonic parameter identification device, subsynchronous/supersynchronous harmonic parameter identification equipment and medium | |
| CN110456159B (en) | System side harmonic impedance estimation method and system based on corrected independent random vector | |
| CN112710899B (en) | Power grid signal frequency detection method for improving gain finite impulse response filtering | |
| CN111896802B (en) | Frequency self-adaptive sampling method | |
| Djurovic | Estimation of the sinusoidal signal frequency based on the marginal median DFT | |
| CN110320400B (en) | Voltage flicker envelope parameter extraction method for quasi-synchronous sampling and improved energy operator | |
| CN105137198A (en) | Novel dielectric loss measurement method based on Nuttall window - five-point converting FFT | |
| CN112986680A (en) | Coordinate transformation-based voltage sag rapid detection method and system | |
| CN111624408B (en) | Power line ground capacitance real-time measurement method based on symbiotic multi-functional calculation | |
| CN114487589A (en) | Power grid broadband signal self-adaptive measurement method, device and system | |
| CN110007129B (en) | A kind of three-phase voltage real-time estimation method applied to dynamic electric energy metering | |
| Serov et al. | A research on the influence of non-ideal analog-to-digital converter on the measurement error of frequency | |
| CN113675883A (en) | Method for identifying control delay parameters of grid-connected inverter | |
| CN112362968A (en) | Single-phase harmonic real-time extraction method based on pre-modulation CDSC and SDFT | |
| CN114184838A (en) | Power system harmonic detection method, system and medium based on SN mutual convolution window | |
| CN112557751A (en) | Harmonic parameter estimation method based on DFT iteration method | |
| CN112485522A (en) | Flat-top window function synchronous phasor measurement method and device based on electric energy data sensing | |
| CN112255457A (en) | Phase angle difference measuring method suitable for automatic quasi-synchronization device | |
| CN106980043A (en) | A kind of improvement phase difference correction method based on Hanning window |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |